Symmetric Magic Squares and Multivariate Splines

G/SPLINES: A Hybrid of Friedman's Multivariate Adaptive Regression Splines (MARS) Algorithm with Holland's Genetic Algorithm

G/SPLINES ate a hybrid of Friedman's Multivariable Adaptive Regression Splines (MARS) algorithm with Holland's Genetic Algorithm. In this hybrid, the incremental search is replaced by a genetic search. The G/SPLINE algorithm exhibits performance comparable to that of the MARS algorithm, requires fewer least-squares computations, and allows significantly larger problems to be considered.

Developing a Regression Algorithm for Predicting Magic: The Gathering Card Efficiency in Draft Format

This paper seeks to predict efficiency ratings for Magic: The Gathering cards in the Draft format. This paper first uses reliable data gathered from the Magic community as the true efficiency ratings. Then, this paper discusses which of the available features are used and the reasoning behind using or not using a feature. This paper then examines a variety of regression algorithms to determine ...

Strongly symmetric self-orthogonal diagonal Latin squares and Yang Hui type magic squares

Keywords: Self-orthogonal Latin square Strongly symmetric Magic square Yang Hui type a b s t r a c t In this paper, a strongly symmetric self-orthogonal diagonal Latin square of order n with a special property (* SSSODLS(n)) is introduced. It is proved that a * SSSODLS(n) exists if and only if n ≡ 0 (mod 4) and n ̸ = 4. As an application, it is shown that there exists a Yang Hui type magic squar...

Magic Labelings of Graphs , Symmetric Magic Squares , Systems of Parameters , and Cohen - Macaulay Rings Richard

Extended Linear Models, Multivariate Splines and Anova

Extended Linear Models, Multivariate Splines and ANOVA by Mark Henry Hansen Doctor of Philosophy in Statistics University of California at Berkeley Professor Charles J. Stone, Chair In this dissertation, we pursue a theoretical investigation into several aspects of multivariate function estimation. In general, we con ne ourselves to estimators that are smooth, piecewise polynomial functions, or...